Evidence map›Paper›PMID 41662068›Full record

ArticlePLOS mental health2026

An ecological model in support of an ontology of mental functioning.

Maryanne J Sacco, Guy Divita, Kathleen Coale, Howard H Goldman, Carolyn P Rosé

Abstract read
In one paragraph

Article in PLOS mental health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Maryanne J SaccoRehabilitation Medicine Department, Clinical Center, National Institutes of Health, Bethesda, Maryland, United States of America.ORCID https://orcid.org/0009-0009-1588-5677
Guy DivitaRehabilitation Medicine Department, Clinical Center, National Institutes of Health, Bethesda, Maryland, United States of America.
Kathleen CoaleRehabilitation Medicine Department, Clinical Center, National Institutes of Health, Bethesda, Maryland, United States of America.ORCID https://orcid.org/0009-0004-7367-6746
Howard H GoldmanRehabilitation Medicine Department, Clinical Center, National Institutes of Health, Bethesda, Maryland, United States of America.
Carolyn P RoséRehabilitation Medicine Department, Clinical Center, National Institutes of Health, Bethesda, Maryland, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Health records contain rich sources of mental health data that can be used to evaluate disability and health care outcomes. However, a lack of behavioral health ontologies focused on daily life activity functioning has impeded development of clinical informatic tools to extract mental functioning information. We aim to present the theoretical foundation and conceptual model upon which the Ecological Mental Functioning Ontology (EMFO) was built to facilitate natural language processing (NLP) to extract mental functioning information in free-text clinical records. Subject matter experts operationally defined mental functioning, and a related theoretical perspective was established. Face validity of a proposed model was obtained using an iterative grounded theory approach. An annotation schema based on the model was constructed and tested using manual annotation and consensus on datasets of real and synthetic clinical notes. An annotation schema, based on the Ecological Model of Mental Functioning (EMMF), was shown to be robust when using NLP methods to identify and extract mental functioning information in real and synthetic behavioral health clinical notes. Mental functioning is a complex phenomenon that is fully conceptualized within an ecological milieu encompassing the dynamic transactive relationship between the person, the nature and demands of activities the person participates in, and the external contextual and environmental factors within which the activities take place. By operationalizing mental functioning, the EMMF provided a conceptual roadmap to develop the EMFO and NLP methods that identify and extract mental functioning activity information in clinical records.

Identifiers

PMID41662068
PMCPMC12810788

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.